Hoist DigiSoft builds data platforms, dashboards and secure integrations for companies in healthcare, financial services and insurance, retail and ecommerce, manufacturing, logistics, SaaS, professional services and real estate. The method is the same everywhere; what changes is the systems we connect, the KPIs we model and the rules we design around.
Which industries do we work with?
| Industry | Systems we typically connect | KPIs we typically model | Rules we design around |
|---|---|---|---|
| Healthcare | EHR, billing, scheduling, patient engagement | Visit volume, no-show rate, days in A/R, denial rate | Health privacy law, minimum-necessary access |
| Financial services & insurance | Core, policy admin, claims, CRM, GL | Loss ratio, claims cycle time, AUM, delinquency | Audit trails, retention, financial privacy rules |
| Retail & ecommerce | Shopify, POS, ad platforms, 3PL/WMS, accounting | Contribution margin, CAC, LTV, sell-through | Card data kept out of scope, consumer privacy |
| Manufacturing | ERP, MES, quality, IoT/sensors | OEE, scrap rate, downtime, cost per unit | Customer and supplier data obligations |
| Logistics & supply chain | TMS, WMS, telematics, carrier portals | On-time delivery, cost per shipment, dwell time | Customer contract and data-sharing terms |
| SaaS & technology | Product analytics, billing, CRM, support | MRR, net revenue retention, churn, activation | Customer data agreements, SOC 2 readiness |
| Professional services | Time tracking, PSA, accounting, CRM | Utilization, realization, project margin, WIP | Client confidentiality |
| Real estate | Property management, leasing, accounting, IoT | Occupancy, NOI, rent collection, lease expiry | Tenant personal information |
Healthcare
Clinics and multi-site health organizations run on an EHR, a billing system and a scheduling tool that rarely share a clean view. We unify them in a secured warehouse with dashboards for operations and revenue, designed around health privacy rules from the first day.
Healthcare data analytics consulting
Financial services & insurance
The data problem. Lenders, wealth managers, insurers and brokers often run a core or policy system, a separate claims or servicing tool, a CRM and a general ledger, with month-end reporting stitched together in spreadsheets. Regulators and auditors want to know where every number came from.
What we build:
– a governed warehouse combining policy, claims, customer and GL data, with history so you can report “as at” any date;
– finance and risk dashboards: loss ratio, claims cycle time, delinquency, AUM and flows, product profitability;
– predictive models for lapse, late payment and anomaly flags, routed to a person for review;
– data lineage and audit trails, so each reported figure can be traced to source;
– encryption and key management for account, policy and identity data.
Rules we design around. Financial privacy and security expectations such as GLBA in the US, PIPEDA in Canada, and the Privacy Act 1988 and APRA CPS 234 for regulated entities in Australia. We implement the data controls and help you document them; we don’t certify compliance. See data security and encryption.
Common use cases: single source of truth for finance · automated reporting
Retail & ecommerce
Brands and retailers selling across Shopify, stores, marketplaces and wholesale need one view of orders, margin, inventory and customers. We connect storefront, POS, ad, 3PL and accounting data so contribution margin and stock cover are visible daily.
Retail & ecommerce analytics consulting
Manufacturing, logistics & supply chain
Manufacturers and logistics operators run ERP, MES, WMS, TMS and sensor data in separate worlds. We bring them together to track OEE, downtime, inventory, cost per unit and on-time delivery in one place, and to forecast demand.
Manufacturing & logistics analytics consulting
SaaS & technology
The data problem. Software companies have more data than most and still argue about MRR. Product usage sits in an analytics tool or the app database, subscriptions in Stripe or a billing platform, pipeline in the CRM and tickets in a support desk. Board metrics get rebuilt by hand every quarter.
What we build:
– a warehouse joining product events, subscriptions, CRM and support data at the account level;
– one agreed definition each for MRR, ARR, net revenue retention, gross churn and expansion, in a semantic layer;
– customer 360 views: usage, revenue, health and open tickets per account;
– churn and expansion models, with scores written back to the CRM through reverse ETL;
– data-layer controls (encryption, access, logging) that support SOC 2 readiness.
Rules we design around. Customer data processing agreements, data residency commitments to customers, and SOC 2 expectations. See data security.
Related services: data integration · business intelligence · data mining & predictive analytics
Professional services
The data problem. Consulting, accounting, legal, engineering and agency firms sell time and expertise. Time sits in a tracking tool or PSA, invoices in accounting, pipeline in the CRM and staffing plans in spreadsheets. Utilization and project margin are often a month late and argued over.
What we build:
– a warehouse joining time, billing, project, CRM and HR data;
– firm, practice and individual dashboards for utilization, realization, WIP, project margin and pipeline coverage;
– automated reporting to replace the weekly utilization spreadsheet;
– application integrations so won deals create projects and invoices without re-keying;
– row-level security so partners, practice leads and staff see the right slice.
Rules we design around. Client confidentiality and engagement terms: client names and matter data visible only to the people who need them, with access logged.
Related services: business intelligence · Power BI consulting
Real estate
Owners, operators and property managers run leasing, property management, accounting and building systems that rarely line up. We connect them for live occupancy, rent collection, NOI and asset performance dashboards.
Real estate data analytics & BI
Is your industry missing?
The method works in any sector with more than a handful of systems. If yours isn’t listed, the audit is the quickest way to find out whether we’re a fit, and we’ll tell you honestly if we’re not.
Your systems, your KPIs, your rules.
Book a free 30-minute data audit and we’ll map your systems and the KPIs that matter in your industry.